Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "72"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 72 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 34 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 32 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 72, Node N04:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459849 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 5.120988 -0.047779 0.231616 2.276854 0.729421 0.847685 4.224641 -0.919807 0.7538 0.7673 0.3345 3.954871 3.264341
2459848 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 5.455758 0.315058 -0.332744 1.953983 2.868572 0.512514 1.355371 -0.698851 0.7307 0.7684 0.3562 3.432040 2.903607
2459847 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 5.385550 0.242377 -0.482259 2.359695 1.600871 0.254344 1.446241 -0.772847 0.7319 0.7074 0.4096 3.538916 2.939863
2459846 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 6.740728 -0.843480 0.231330 2.513828 0.256139 0.733640 1.749586 -0.703331 0.8553 0.7081 0.4436 3.560158 2.900062
2459845 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 6.511194 0.305396 0.541800 3.469741 1.598021 0.992584 10.237398 -0.467183 0.7402 0.7640 0.3601 16.251941 36.304866
2459844 digital_ok 100.00% 0.00% 0.00% 0.00% - - 38.424467 51.275607 93.156976 110.863856 262.041704 225.625252 58.750752 54.561811 0.8825 0.6300 0.5734 nan nan
2459843 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 8.565153 0.180660 -0.673490 0.372974 70.876600 81.654332 12.431728 0.329012 0.7550 0.7691 0.3752 4.580657 3.636482
2459838 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 68.180054 63.039408 67.469852 71.626450 68.516764 104.042383 634.576751 752.140789 0.0184 0.0168 0.0011 0.813894 0.805595
2459833 digital_ok 100.00% 0.00% 0.00% 0.00% - - 15.907395 19.204526 28.828414 32.516680 313.831405 287.818811 43.249272 30.952028 0.7341 0.4585 0.5089 nan nan
2459832 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 5.257168 -0.680048 -0.821762 0.973286 0.145441 0.925396 2.774753 -0.971438 0.0970 0.0830 0.0151 1.206210 1.208930
2459831 digital_ok 100.00% 100.00% 100.00% 0.00% - - -0.856848 -0.405035 -0.488023 3.982738 0.937315 -0.329987 1.696374 1.203954 0.0323 0.0371 0.0009 nan nan
2459830 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 5.505755 -1.049080 -0.789439 1.407915 3.183383 -0.825843 4.539166 -1.207966 0.0957 0.0686 0.0140 1.226195 1.223577
2459829 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 7.729247 -0.271854 -0.631210 0.825063 1.512398 0.555522 7.736295 -0.995937 0.0792 0.0709 0.0111 6.216159 10.771415
2459828 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 3.606530 -0.616560 -0.618729 0.504790 3.976918 -0.594447 4.823386 -1.053786 0.1014 0.0771 0.0158 1.246435 1.248741
2459827 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 5.653505 -0.401279 -0.421397 1.954498 1.284032 0.441090 6.968338 3.673110 0.0847 0.0779 0.0130 1.237231 1.232689
2459826 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 3.869640 -0.951539 -0.332650 2.025250 4.323041 -0.567175 5.332582 -1.111612 0.0886 0.0785 0.0172 0.951513 0.953645
2459825 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 3.807696 -0.694903 -0.751555 1.066199 1.311611 -0.923016 4.163518 -0.246065 0.1061 0.0896 0.0195 1.207357 1.193451
2459824 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% 3.986092 -0.055399 -0.678177 1.496756 0.955029 -0.152017 1.222230 -0.837659 0.0796 0.0744 0.0122 1.170652 1.165635
2459823 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% 1.125065 -0.657474 -0.697792 1.883983 -0.343370 1.756559 1.868401 -1.509048 0.0890 0.0743 0.0119 1.125285 1.125856
2459822 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 3.573627 -0.841520 -0.621610 1.482194 1.386167 -0.341102 6.634668 4.188646 0.1147 0.1016 0.0202 1.154528 1.151649
2459821 digital_ok 0.00% 11.29% 11.29% 0.00% 13.16% 60.53% 3.190428 -0.620855 -0.697152 1.597476 1.412981 -0.410916 2.708131 -0.004376 0.7323 0.6064 0.4233 3.592948 3.023811
2459820 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 4.328342 -0.456575 -0.622889 1.455982 3.501769 1.003664 5.900627 -0.718279 0.7821 0.7120 0.3928 4.101593 3.813323
2459817 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 55.26% 2.216198 -1.436970 -0.461257 0.952967 0.364642 0.523069 -0.094568 -0.836959 0.8301 0.7097 0.4805 2.453931 2.115073
2459816 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 76.74% 3.548312 -0.959766 -0.845555 1.809948 0.976436 1.360679 0.905524 -1.138694 0.8494 0.6293 0.5586 3.821007 3.293824
2459815 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 57.89% 2.455962 -0.823916 -0.847435 1.503651 1.016628 1.342223 3.891432 -1.152500 0.8253 0.7134 0.4956 3.180371 2.697083
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 7.584946 -0.744531 -0.698578 1.114648 2.707307 0.316794 4.853688 -0.262671 0.8026 0.7381 0.3980 15.656179 12.038925

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 72: 2459849

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Shape 5.120988 5.120988 -0.047779 0.231616 2.276854 0.729421 0.847685 4.224641 -0.919807

Antenna 72: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Shape 5.455758 0.315058 5.455758 1.953983 -0.332744 0.512514 2.868572 -0.698851 1.355371

Antenna 72: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Shape 5.385550 0.242377 5.385550 2.359695 -0.482259 0.254344 1.600871 -0.772847 1.446241

Antenna 72: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Shape 6.740728 6.740728 -0.843480 0.231330 2.513828 0.256139 0.733640 1.749586 -0.703331

Antenna 72: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Temporal Discontinuties 10.237398 0.305396 6.511194 3.469741 0.541800 0.992584 1.598021 -0.467183 10.237398

Antenna 72: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Temporal Variability 262.041704 38.424467 51.275607 93.156976 110.863856 262.041704 225.625252 58.750752 54.561811

Antenna 72: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok nn Temporal Variability 81.654332 0.180660 8.565153 0.372974 -0.673490 81.654332 70.876600 0.329012 12.431728

Antenna 72: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok nn Temporal Discontinuties 752.140789 63.039408 68.180054 71.626450 67.469852 104.042383 68.516764 752.140789 634.576751

Antenna 72: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Temporal Variability 313.831405 19.204526 15.907395 32.516680 28.828414 287.818811 313.831405 30.952028 43.249272

Antenna 72: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Shape 5.257168 5.257168 -0.680048 -0.821762 0.973286 0.145441 0.925396 2.774753 -0.971438

Antenna 72: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
72 N04 digital_ok nn Power 3.982738 -0.856848 -0.405035 -0.488023 3.982738 0.937315 -0.329987 1.696374 1.203954

Antenna 72: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Shape 5.505755 5.505755 -1.049080 -0.789439 1.407915 3.183383 -0.825843 4.539166 -1.207966

Antenna 72: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Temporal Discontinuties 7.736295 -0.271854 7.729247 0.825063 -0.631210 0.555522 1.512398 -0.995937 7.736295

Antenna 72: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Temporal Discontinuties 4.823386 -0.616560 3.606530 0.504790 -0.618729 -0.594447 3.976918 -1.053786 4.823386

Antenna 72: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Temporal Discontinuties 6.968338 5.653505 -0.401279 -0.421397 1.954498 1.284032 0.441090 6.968338 3.673110

Antenna 72: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Temporal Discontinuties 5.332582 -0.951539 3.869640 2.025250 -0.332650 -0.567175 4.323041 -1.111612 5.332582

Antenna 72: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Temporal Discontinuties 4.163518 -0.694903 3.807696 1.066199 -0.751555 -0.923016 1.311611 -0.246065 4.163518

Antenna 72: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Shape 3.986092 3.986092 -0.055399 -0.678177 1.496756 0.955029 -0.152017 1.222230 -0.837659

Antenna 72: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok nn Power 1.883983 -0.657474 1.125065 1.883983 -0.697792 1.756559 -0.343370 -1.509048 1.868401

Antenna 72: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Temporal Discontinuties 6.634668 3.573627 -0.841520 -0.621610 1.482194 1.386167 -0.341102 6.634668 4.188646

Antenna 72: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Shape 3.190428 -0.620855 3.190428 1.597476 -0.697152 -0.410916 1.412981 -0.004376 2.708131

Antenna 72: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Temporal Discontinuties 5.900627 4.328342 -0.456575 -0.622889 1.455982 3.501769 1.003664 5.900627 -0.718279

Antenna 72: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Shape 2.216198 2.216198 -1.436970 -0.461257 0.952967 0.364642 0.523069 -0.094568 -0.836959

Antenna 72: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Shape 3.548312 -0.959766 3.548312 1.809948 -0.845555 1.360679 0.976436 -1.138694 0.905524

Antenna 72: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Temporal Discontinuties 3.891432 -0.823916 2.455962 1.503651 -0.847435 1.342223 1.016628 -1.152500 3.891432

Antenna 72: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 72: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
72 N04 digital_ok ee Shape 7.584946 -0.744531 7.584946 1.114648 -0.698578 0.316794 2.707307 -0.262671 4.853688
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